An Agent-Based "Virtual Clinical Trial" for the Analysis and Evaluation of COPD Patients Cohorts Behavior

Mohsen Hallaj Asghar; Alvaro Wong; Francisco Epelde; Manel Taboada; Dolores Rexachs; Emilio Luque

doi:10.24215/16666038.24.e13

Authors

Mohsen Hallaj Asghar Computer Architecture and Operating Systems Department, Universitat Autonoma de Barcelona (UAB), Spain
Alvaro Wong Department of Computer Architecture and Operating Systems, Universitat Autonoma de Barcelona, Barcelona, Spain https://orcid.org/0000-0002-8394-9478
Francisco Epelde Consultant Internal Medicine, Universirt Hospital Parc Tauli, Universitat Autonoma de Barcelona, Sabadell, Barcelona, Spain
Manel Taboada Escoles Universitaries Gimbernat (EUG), Computer Science School, Universitat Autonoma de Barcelona, Sant Cugat del Valle ́s Barcelona, Barcelona, Spain https://orcid.org/0000-0003-3348-8404
Dolores Rexachs Department of Computer Architecture and Operating Systems, Universitat Autonoma de Barcelona, Barcelona, Spain https://orcid.org/0000-0001-5500-850X
Emilio Luque Department of Computer Architecture and Operating Systems, Universitat Autonoma de Barcelona, Barcelona, Spain https://orcid.org/0000-0002-2884-3232

DOI:

https://doi.org/10.24215/16666038.24.e13

Keywords:

Chronic obstructive pulmonary disease (COPD), agent based model, Cohort-based strategies, Virtual clinical trial

Abstract

Chronic Obstructive Pulmonary Disease (COPD) is a chronic respiratory condition characterized by inflammation and narrowing of the airways, leading to symptoms such as shortness of breath, coughing, and chest tightness. Treatment typically involves lifestyle adjustments, medication, and pulmonary rehabilitation to improve lung function and quality of life. This study presents a model examining COPD patient behavior within cohort-based strategies, focusing on how environmental factors impact vital signs across the entire cohort. We developed a comprehensive virtual clinical trial model that encompasses study protocol design, participant recruitment, virtual data collection, outcome analysis, and conclusions. This includes remote symptom monitoring, virtual healthcare consultations, treatment adherence assessments, and research data collection. Additionally, we explore the influence of external variables such as environmental conditions, comorbidities, and lifestyle factors on chronic disease symptoms and disease stability. We used an Agent-Based Model(ABM) to incorporate these factors to assess COPD progression and treatment efficacy. Individual agents represent COPD patients, each characterized by attributes such as age, smoking history, lung function, comorbidities, and treatment plans.

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References

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